MODELLING OF ATMOSPHERIC FLOW AND DISPERSION IN THE WAKE OF A CYLINDRICAL OBSTACLE

This paper presents computational simulations of atmospheric dispersion experiments conducted around isolated obstacles in the field. The computational tool used for the simulations was the code ADREA-HF, which was especially developed for the simulation of the dispersion of positively or negatively buoyant gases in complicated geometries. The field experiments simulated involve a single cylindrical obstacle normal to the mean wind direction and two upwind sources of ammonia and propane, with the ammonia source located at different lateral positions (Mavroidis et al., 2003). Concentrations and concentration fluctuations for both gases were calculated by the model and compared with the experimental results to evaluate the model performance. Specific characteristics of dispersion were investigated using the computational tool. Comparisons of experimental and model results with the case of dispersion around an isolated cubical obstacle are also presented and discussed

Evaluation of dispersion models DIPCOT and RIMPUFF used in Decision Support Systems for nuclear and radiological emergency response

This paper presents evaluation of the atmospheric dispersion models DIPCOT and RIMPUFF which are incorporated for operational use in Decision Support Systems for nuclear emergencies. The evaluation is performed through comparisons of model results with real-scale measurements of gamma radiation dose rates in air obtained during the routine operation of the HIFAR Research Reactor located in Sydney, Australia. The area surrounding the reactor is characterized by moderately complicated topography and varying land cover. A total of 16 days have been computationally simulated, covering all atmospheric stability conditions. Qualitative and quantitative model evaluation is carried out, using comparisons of paired in space and time calculated and measured gamma dose rates, statistical indices, scatter plots, and contour plots. The models performance is satisfactory for a number of cases, while for others the performance is poor. This can be attributed to a number of factors, mainly uncertainties in the prediction of meteorological conditions

MODELLING THE CONCENTRATION FLUCTUATION AND INDIVIDUAL EXPOSURE IN COMPLEX URBAN ENVIRONMENTS

The concentrations fluctuations of a dispersing hazardous gaseous pollutant in the atmospheric boundary layer, and the hazard associated with short-term concentration levels, demonstrate the necessity of estimating the magnitude of these fluctuations using predicting models. Moreover the computation of concentration fluctuations and individual exposure in case of dispersion in realistic situations, such as built-up areas or street canyons, is of special practical interest for hazard assessment purposes. In order to predict or/and estimate the maximum expected dosage and the exposure time within which the dosage exceeds certain health limits, the knowledge of the behaviour of concentration fluctuations at the point under consideration is needed. In this study the whole effort is based on the ‘Mock Urban Setting Test – MUST’, an extensive field test carried out on a test site of the US Army in the Great Basin Desert in 2001 (Biltoft, 2001; Yee, 2004). The experimental data that was used for the model evaluation concerned the dispersion of a passive gas between street canyons which have been created by 120 standard size shipping containers. The computational simulations have been performed using the laboratory CFD code ADREA, which has been developed for simulating the dispersion and exposure of pollutants over complex geometries. The ADREA model is evaluated by comparing the model’s predictions with the observations utilizing statistical metrics and scatter plots. The present study has been performed in the frame of the Action COST 732 “Quality Assurance and Improvement of Micro-Scale Meteorological Models”

Improvement of source and wind field input of atmospheric dispersion model by assimilation of concentration measurements: Method and applications in idealized settings

AbstractThe problem of correcting the pollutant source emission rate and the wind velocity field inputs in a puff atmospheric dispersion model by data assimilation of concentration measurements has been considered. Variational approach to data assimilation has been used, in which the specified cost function is minimized with respect to source strength and/or wind field. The analyzed wind field satisfied the constraints derived from the conditions of mass conservation and linearized flow equations for perturbations from the first guess wind field. ‘Identical twin’ numerical experiments have been performed for the validation of the method. The first guess estimation errors of source emission rate and wind field were set to a factor of up to 10 and up to 6m/s respectively. The calculations results showed that in most studied cases an improvement of vector wind difference (VWD) error by about 0.7–1m/s could be achieved. The resulting normalized mean square error (NMSE) of concentration field was also reduced significantly

A statistical model for the prediction of wind-speed probabilities in the atmospheric surface layer

Wind fields in the atmospheric surface layer (ASL) are highly three-dimensional and characterized by strong spatial and temporal variability. For various applications such as wind comfort assessments and structural design, an understanding of potentially hazardous wind extremes is important. Statistical models are designed to facilitate conclusions about the occurrence probability of wind speeds based on the knowledge of low-order flow statistics. Being particularly interested in the upper tail regions we show that the statistical behavior of near-surface wind speeds is adequately represented by the Beta distribution. By using the properties of the Beta probability density function in combination with a model for estimating extreme values based on readily available turbulence statistics, it is demonstrated that this novel modelling approach reliably predicts the upper margins of encountered wind speeds. The model’s basic parameter is derived from three substantially different calibrating datasets of flow in the ASL originating from boundary-layer wind-tunnel measurements and direct numerical simulation. Evaluating the model based on independent field observations of near-surface wind speeds showed a high level of agreement between the statistically modelled horizontal wind speeds and measurements. The results show that, based on the knowledge of only a few simple flow statistics (mean wind speed, wind speed fluctuations and integral time scales), the occurrence probability of velocity magnitudes at arbitrary flow locations in the ASL can be estimated with a high degree of confidence

APPLICATION OF ADJOINT CMAQ CHEMICAL TRANSPORT MODEL IN THE ATHENS GREATER AREA: SENSITIVITIES STUDY ON OZONE CONCENTRATIONS

An operational meteorology and air quality forecasting system is currently under development by the Environmental Research Laboratory of NCSR “Demokritos”. The system is based on the meteorological model MM5, the in-house EMISLAB emissions processing system and the chemical transport model CMAQ. It is configured to apply on the Greater Athens Area with a 4-domains nested configuration focusing on a high spatial resolution (1x1 km2) inner domain. The system produces meteorological and air quality predictions for a 72-hours time horizon with 1 hour time step. This paper uses the output of the operational system to apply the CMAQ adjoint for ozone sensitivity calculations, focusing for the two days of 18 and 19 July 2005. In the current study, the calculated ground level ozone concentrations at certain defined locations and times are considered as the “response functional”. Sensitivities of the response functional with respect to the state variables (species concentrations on the grid points and species emissions, e.g., NOX, CO, VOCs) are calculated by running the adjoint model backwards in time (reverse mode). The distribution of the sensitivities in the computational domain, obtained for different times, provides essential information for the analysis: isosurfaces of sensitivities delineate influence regions, i.e., areas where perturbations in some concentrations will result in significant changes in the ozone concentrations in the area of interest at the final time

Radiation source rate estimation through data assimilation of gamma dose rate measurements for operational nuclear emergency response systems

This paper presents an evaluation of an innovative data assimilation method that has been recently developed in NCSR Demokritos for estimating an unknown emission rate of radionuclides in the atmosphere, with real-scale experimental data. The efficient algorithm is based on the assimilation of gamma dose rate measured data in the Lagrangian atmospheric dispersion model DIPCOT and uses variational principles. The DIPCOT model is used in the framework of the nuclear emergency response system (ERS) RODOS. The evaluation is performed by computational simulations of dispersion of Ar-41 that was emitted routinely by the Australian Nuclear Science and Technology Organisation’s (ANSTO) previous research reactor, HIFAR, located in Sydney, Australia. In this paper the algorithm is evaluated against a more complicated Radiation source rate estimation through data assimilation 387 case than the others used in previous studies: There was only one monitoring station available each day and the site topography is characterised as moderately complex. Overall the estimated release rate approaches the real one to a very satisfactory degree as revealed by the statistical indicators of errors. © 2012 Inderscience Enterprises Ltd